Is deep learning a subset of machine learning?
Yes
No
Maybe
It depends
What is the purpose of preparing data for machine learning?
To clean and transform data for optimal model performance
To generate predictions
To reduce the dataset size
To perform feature extraction
What is the purpose of the elbow method in K-means clustering?
To determine the optimal number of clusters
To speed up the clustering process
To visualize the clusters
To perform feature selection
What is a key benefit of open-source LLMs for commercial use?
They are always more accurate
They allow customization and transparency
They are always faster
They require no licensing
What is the purpose of the Kullback-Leibler divergence in machine learning?
To perform classification
To measure the difference between probability distributions
To reduce dimensionality
To generate synthetic data
What is the primary difference between machine learning and traditional programming?
ML requires more computational power
ML learns from data, traditional programming follows explicit instructions
ML only works with numerical data
ML is always more accurate than traditional programming
Which statement about machine learning is true?
It improves with more data
It does not require data
It is static and unchangeable
It always uses deep learning
What is the purpose of the Earth Mover's Distance (EMD) in machine learning?
To perform classification
To measure the distance between probability distributions
To reduce dimensionality
To generate synthetic data
What are applications for machine learning in automotive industry?
Only for manufacturing
Only for design
Autonomous driving, predictive maintenance, and more
It's not used in automotive industry
What does SGD stand for in machine learning?
Supervised Gradient Descent
Stochastic Gradient Descent
System Generalization Design
Standard Gaussian Distribution
What is deep machine learning?
A subset of machine learning using neural networks with many layers
A type of unsupervised learning
A method for data preprocessing
A technique for model deployment
What is a grid search in machine learning?
A technique to find the best hyperparameters for a model
A clustering algorithm
A data preprocessing tool
A method to reduce data dimensionality
What is the purpose of the Word2Vec algorithm in natural language processing?
To perform sentiment analysis
To generate word embeddings
To translate between languages
To summarize text
What is the difference between large language models (LLMs) and traditional machine learning models?
LLMs are more accurate
LLMs are less accurate
LLMs are more complex
LLMs are less complex
How does machine learning differ from rule-based systems?
ML learns from data, rule-based systems use explicit rules
Rule-based systems learn from data, ML uses explicit rules
Both are the same
ML does not use data at all
What is a decision tree in machine learning?
A model that splits data based on features to predict outcomes
A method to cluster similar items
A tool for data visualization
A technique to reduce dimensionality
What is the main idea behind the YOLO (You Only Look Once) algorithm?
It's a type of RNN
It's a real-time object detection system
It's a clustering algorithm
It's a technique for data augmentation
What type of deep learning algorithms are typically used by generative AI?
Convolutional Neural Networks
Recurrent Neural Networks
Generative Adversarial Networks
Decision Trees
What are embeddings in NLP?
A type of punctuation
Vector representations of words or phrases
A method of text encryption
A form of data compression
What is LCEL in LangChain?
Language Chain Encryption Layer
LangChain Expression Language
Linguistic Computation Evaluation Logic
Learning Chain Execution Loop
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